AllianceChicago CIO Discusses Technology-Driven Approaches to Health Equity

AllianceChicago is a unique organization. A federally funded health center network of more than 76 community health centers operating in more than 23 states. Its work is focused on improving personal, community, and public health through innovative collaboration.

The collaboration has existed for more than 25 years and focuses on developing and implementing systems that promote equality and optimize health and well-being.

It does this by supporting the development and optimal use of health information technology, conducting rigorous community-based research and evaluation, and developing innovative partnerships with health centers and stakeholders to explore new ways to promote the health of individuals and communities.

CHCs are ahead of the rest of the healthcare world when it comes to understanding the impact of social determinants of health and applying the knowledge to support the communities they serve. For example, Andrew Hamilton, RN, CIO and deputy director of AllianceChicago, and his team partnered with the National Association of Community Health Centers to develop a tool called PRAPARE, which is used by most CHCs in the U.S.

Healthcare IT News spoke to Hamilton to discuss some of the issues that all healthcare providers can learn from. We talked about how healthcare information technology is helping to promote equity, the role of healthcare-generated data in supporting population health monitoring, and the collection and use of data on needs in social care.

Q. Health equity is a major and important issue that needs to be addressed. How can health information technology help to promote equity?

A. The IOM (now the National Academy of Medicine) has defined six domains of health care quality where health information technology can play an important role: safe, effective, patient-centered, timely, efficient, and equitable.

It is well known that health IT is a critical aspect of each of these domains of health care. With respect to health IT and equity, the techquity framework provides an approach to the strategic design, development, and deployment of technology to advance health equity. It embraces the idea that technology can either support or hinder progress in health equity if not implemented in an intentional and inclusive manner.

It is also important to note that tech equity is not an issue at the “individual or consumer level.” Promoting or advancing tech equity requires collaboration, transparency, inclusivity, and a commitment to ensuring organizational transformation at a systemic level to achieve equitable care.

Three key elements of health IT are needed to optimize technology to promote equity in care: unimpeded access, use (uptake and usability), and sustained engagement. These factors that influence techquity are strongly correlated with health-related social needs, including (but not limited to) access to internet/broadband services, affordability of technology services and assistive devices, accessibility of languages ​​(other than English and Spanish), and digital and health literacy.

In other words, the design and deployment of health IT must take these health-related needs into account so that technology promotes equitable care.

Q. Public health is an important topic for everyone in healthcare to support. What is the role of healthcare-generated data in supporting public health surveillance?

A. The COVID pandemic has presented several opportunities to strengthen both our health care system and our public health infrastructure. In terms of oversight, the U.S. public health system has been largely informed by vital records (birth/death certificates, mandatory case reports, laboratory data), survey data (consumers, health care providers, insurance companies), environmental monitoring (water and air quality), and animal health (veterinarians, farms, and food producers).

A key issue in each of these domains is the timeliness, consistency, and interoperability of information. These factors significantly impact the overall time to access, process, and analyze this data, hampering a timely and coordinated public health response, particularly during an outbreak of a new disease.

When it comes to electronic health systems, there is a clear opportunity to modernize the public health surveillance infrastructure, particularly thanks to advances in data standardization and interoperability that underlie the 21st Century Cures Act, which in part regulates EHR systems.

AllianceChicago, in collaboration with the National Association of Chronic Disease Directors and other partners, recently completed a five-year CDC-funded demonstration project that established an EHR disease surveillance system to both inform public health surveillance and demonstrate how a shared system between public health and health care can improve monitoring, coordination of public health surveillance and response.

There have been similar efforts demonstrating the use of EHR data to support public health, including pediatric obesity, sexually transmitted infections, and maternal health outcomes. It is clear from all of these programs that EHR data are a vital and rich asset to support public health surveillance.

I believe the next critical phase of work will be to harmonize these efforts and develop a path to scale these networks and include additional data providers to ensure adequate and fair representation of the U.S. population and to integrate data sources related to societal determinants of health.

Q. You are passionate about addressing social care needs. Discuss the collection and use of data on social care needs..

A. It is clear from both my previous answers that in order to develop a person-centred, fair health system (including the public health system) it is crucial to collect, analyse and develop coordinated responses to social care needs. This is a key aspect of improving health outcomes and equity.

There is increasing evidence that a ‘mixed methods’ approach is needed when collecting data on social care needs. That is, information should be collected directly from those receiving care and data on social care needs at the population level (e.g. risk indices) should be used.

The challenge with individually collected data on social care needs is that it is often a snapshot of the individual (collected at the point in time when the person is receiving care). If individual circumstances change over time, the data may give a false picture of need at a particular point in time.

That said, population-level social care needs data are an estimate of the people in the focus population and may therefore over- or under-estimate an individual’s needs. In addition to data collection issues, work is underway to standardise these data to ensure comparability and interoperability of the data.

Standardization work, such as that of Gravity Project, is critical to ensuring that data can be processed, analyzed, and shared in a consistent and meaningful way. Collecting and standardizing data are critical components to ensuring optimal and effective use of data.

At the individual level, significant use of social care needs data is related to the inclusion of social care needs in the patient’s overall care plan. Our understanding of the most effective and efficient way to use these data in developing a care plan is evolving.

While we still have much to learn, we have several examples from the field, including the inclusion of support for access to housing, food and transportation. Interventions in social care needs often require cross-sectoral data sharing and collaboration, which also requires changes at the system and community level, which is challenging.

In addition to using these data at the individual level, health systems are learning how to use these data at the population level, which is critical to both improving overall outcomes and health equity. Finally, the relationship between population health and population health provides a clear opportunity to coordinate health system-level interventions with population health programs.

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